The invention relates generally to the field of computer graphics, and in particular to a system and method of integrating a base image, such as a photograph, and a computer generated 3D scene.
The use of interactive and dynamic 3D computer graphics is becoming prevalent in the computing world. Typically, 3D visualization applications provide photo-realistic results using techniques such as ray tracing, radiosity, global illumination and other shading, shadowing and light reflection techniques. Such 3D visualization applications provide a 3D generated model, without relationship to the existing environment.
U.S. patent application Ser. No. 11/538,103 to Elsberg et al, entitled “Method and Apparatus for Virtual Reality Presentation of Civil Engineering, Land Planning and Infrastructure”, published as US 2007/0078636 A1, the entire contents of which are incorporated herein by reference, is addressed to a computer implemented method of visualizing an infrastructure. Such a method allows for evaluating large scale designs in a virtual reality environment.
In the real world, designs such as civil engineering or architectural projects are developed within an existing landscape, which will be impacted by the project. In order to properly visualize the appearance and impact of these designs, preferably any 3D generated model should allow for integration within the existing landscape. Unfortunately, existing modeling programs are not designed to integrate with existing landscape imaging.
An article by Roger Y. Tsai entitled “A Versatile Camera Calibration Technique for High-Accuracy 3D Machine Vision Metrology Using off-the Shelf TV Cameras and Lenses”, published by the Institute of Electrical and Electronics Engineers (IEEE), New York, in the IEEE Journal of Robotics and Automation, Vol. 3, NO. 4, pp. 323-344, 1987, the entire contents of which are incorporated herein by reference, teaches a method for camera calibration, i.e. the recovery of the principle distance and the principle point in the image plane. Tsai's method for camera calibration is cited as recovering the interior orientation, the exterior orientation, the power series coefficients for distortion, and an image scale factor that best fits the measured image coordinates corresponding to known target point coordinates. Thus, from an image or photograph in which the precise location of a number of points is known, the position, orientation and optical information of the camera can be determined.
There is thus a long felt need for an integrated system for rendering a computer generated 3D scene integrated with a base image.